GSE136910 Processing Pipeline

Publication

Circulation (2020) — PMID 32393053

Dataset

RNA Seq of Subcutaneous adipose tissue from endothelial-AGO1-knockout (EC-AGO1-KO) mice and wild-type (WT) littermates

1. 1

   STAR2.6.0a was used to align reads to the genome with default parameters

   STAR v2.6.0a GitHub

   $ Bash example

   # Install STAR (example using conda)
   # conda install -c bioconda star=2.6.0a
   
   # Placeholder for reference genome index directory
   # Replace with the actual path to your STAR genome index for the relevant genome (e.g., hg38, mm10)
   GENOME_INDEX_DIR="/path/to/your/genome/index/hg38"
   
   # Placeholder for input FASTQ file(s)
   # Replace with your actual input FASTQ file(s). For paired-end, use --readFilesIn R1.fastq R2.fastq
   READS_FILE="reads.fastq.gz"
   
   # Placeholder for number of threads
   # Adjust based on available resources
   NUM_THREADS=8
   
   # Placeholder for output file prefix
   OUTPUT_PREFIX="aligned_reads_"
   
   # Align reads to the genome using STAR with default parameters (version 2.6.0a)
   STAR --genomeDir "${GENOME_INDEX_DIR}" \
        --readFilesIn "${READS_FILE}" \
        --runThreadN "${NUM_THREADS}" \
        --outFileNamePrefix "${OUTPUT_PREFIX}"

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2. 2

   Kallisto0.44.0 was used to quantify transcripts abundance in terms of TPM

   Kallisto v0.44.0 GitHub

   $ Bash example

   # Install Kallisto (example using conda)
   # conda install -c bioconda kallisto=0.44.0
   
   # Placeholder for Kallisto index creation (if not already done)
   # Replace 'transcripts.fasta' with your reference transcriptome FASTA file.
   # kallisto index -i transcriptome.idx transcripts.fasta
   
   # Quantify transcripts abundance in terms of TPM
   # Replace 'transcriptome.idx' with your Kallisto index file.
   # Replace 'read1.fastq.gz' and 'read2.fastq.gz' with your actual input FASTQ files.
   # Replace 'output_dir' with your desired output directory.
   kallisto quant -i transcriptome.idx -o output_dir read1.fastq.gz read2.fastq.gz

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Tools Used